The present invention relates generally to processing of data signals. A specific application of the present invention relates to data signal processing involving filtering of asynchronously received data samples. The present invention has application, for example, as part of a radio receiver using digital signal processing circuitry to filter data samples corresponding to signal strength estimates having irregularly timed estimations, where the irregularly timed estimations correspond to the asynchronously received data samples.
Large-user radio communication systems have been developed into a complex inter-networked web of systems deployed to provide coverage internationally. Examples of such systems include cellular radio communication systems and other wireless systems such as wireless LANs. A cellular radio communication system includes multiple communication cells arranged adjacent one another to cover a larger regional area. Each cell limits the number of possible simultaneous communications to the number of channels provided in the cell. The size of the cell is defined through receivers and transmitters (a.k.a., xe2x80x9ctransceiversxe2x80x9d) located within base stations that provide the communication channels through which the mobile radios communicate. A mobile radio communicates in a cellular system by communicating first with a number of close-proximity base stations before selecting the best or nearest base station with which to establish a radio communication link.
In providing a clear channel between the mobile radio and the selected base station, the prevention of interference from and to other radio communication links is an important concern. Generally, this concern is addressed through the use of an accurate method for determining with the nearest base station and by controlling the transmission power levels used in maintaining the communication. If the nearest base station is not accurately selected or changes without a timely update, the communication can overlap and interfere with other communications in the system. Similarly, if the transmission power used in maintaining the radio link within a given cell is not properly controlled at relatively low level, the excessive transmissions can cause intolerable levels of interference. Radio designers have attempted to avoid these problems by designing the mobile radio with a receiver designed to provide precision-selective filtering of the data communicated in such systems; namely, the data communicated between each mobile radio and its surrounding base stations.
Many communication systems, including both cellular systems and the GPS, include receivers that are highly dependent on filters to accurately decipher asynchronously-received data from interference signals, including signals from other radio communication links in the same system. This issue is best explained in the context of a specific system. In cellular communication systems, for instance, the mobile stations select the nearest base station by monitoring a control channel transmitted from each base station for its signal strength and selecting the nearest base station in response to comparing these channel reception levels for the best signal quality. The transmission power is controlled at minimum levels by using algorithms at the base station and/or the mobile radio and, in some systems, also by passing control information between the base station and the mobile radio during the communication. Many of these systems use direct-sequence, spread-spectrum (DSSS) code-division-multiple-access (CDMA) communication. In this type of system, the same frequency is commonly used by a plurality of users by breaking apart the communication and transmitting using different codes. At any given frequency, the signals of other users interfere with the measurements for the signal quality of the transmitting base stations. In an attempt to account for this interference, measurement methods determine the signal quality by computing the ratio of the signal reception level and the interference level, which is known as xe2x80x9cSIRxe2x80x9d or Signal to Interference Ratio, as described for example, by T. Dohi, et al: xe2x80x9cPerformance of SIR Based Power Control in the Presence of Non-uniform Traffic Distribution,xe2x80x9d 1995 Fourth IEEE International Conference on Universal Personal Communications Record, pp. 334-338, November 1995. In addition to the SIR, the signal quality determination is also dependent on the estimates of the signal reception level which, in turn, is dependent on the accuracy in which these estimates are communicated, a problem known as xe2x80x9cmulti-path Rayleigh fading.xe2x80x9d
Multi-path Rayleigh fading (xe2x80x9cfadingxe2x80x9d) is caused by reflections of the signals being received from the base stations through the wireless communication medium. Communication of measured radio frequency (RF) signal strength is also subject to such fading. For cellular CDMA communication systems, the mobile station""s selection of the nearest base station often consists of a search for the optimal CDMA pilot strength. This CDMA pilot strength search is subject to both fading and radio signal interference and is, therefore, particularly susceptible to error. The problem of fading is further aggravated when it is fast fading. Lingering effects of fast fading in signal search results may occur even after coherent and non-coherent integration efforts by the search process, and slower mobile speeds will aggravate this effect more than faster mobile speeds, which is opposite the effect of speed on slow fading signals as it applies to the signal searching process.
It has been determined that the adverse effects of fast fading can be overcome using one or more of the following three approaches: (1) increasing the dwell time to approximate the correlation interval for fast fading; (2) using IIR filtering to average out the effects of residual variance caused by the fading; and (3) searching more frequently to increase the probability of finding a pilot strength signal. Addressing the first of these approaches, the extent of the filter-response distortion in such approaches directly relates to the effect of the dwell time. The correlation time for fast fading is typically half a wavelength. For a 100 Hz dual dwell search, typically the coherent and non-coherent integration times are N=128 and L=16 for the first dwell. The comparison between dwell time and correlation time for different example conditions are given below.
From these comparisons, it can be recognized that the first approach alone, increasing the dwell time to approximate the correlation interval for fast fading, would be insufficient to eliminate the effects of fast fading.
Success of the second and third approaches depends on the effectiveness of the filtering for the particular application at hand. Using the cellular communication system as the target application, the purpose of an idle handoff from one cell to another cell is to provide for the demodulation of stronger pilots signals based on large scale effects like shadowing, while eliminating small scale effects like fast fading. To achieve this, multiple search results within a shadowing correlation time would need to be averaged, while results separated by more than the shadowing correlation time would need to be kept relatively uncorrelated. In connection with the present invention, two approaches have been considered for operation on the time series of consecutive search results to obtain this desired result. The first possibility is to not perform the conventional filtering function. If the search dwell time is significantly higher than the fast fading correlation time, then no further filtering would be needed to achieve the desired averaging of fast fading. However, as can be seen in the above table, the dwell time is typically smaller than the correlation time for fast fading for the 8 kmph cases, typically about the same for the 30 kmph cases, and typically bigger for 100 kmph cases. Hence, the variance due to fading would not be eliminated at this value of dwell time under all fading conditions.
A second possibility is to perform conventional IIR filtering. This method is commonly used in cellular systems for traffic channel search results. Generally, the operation uses a running average of the search results with a certain forgetting factor, which is tantamount to a single pole IIR filter with the appropriate time constant being somewhere between the slow and fast fading correlation times. One potential problem with implementing this filter is in the idle mode, in that the samples would not generally be available in regular intervals; that is, the sampling frequency would dynamically vary based on several factors, including the total number of searches to be performed, search priority, and search window sizes. Moreover, a conventional IIR filter treats a sample arriving relatively quickly the same as a sample arriving relatively late, even though the earlier arriving sample should have more current information. By treating these timed-offset samples equally, the effective time constant the filter used by the filter becomes distorted, thereby distorting the filter""s response.
Accordingly, there is a need for an improved approach to asynchronous signal processing in such communication systems.
According to various aspects of the present invention, embodiments thereof are exemplified in the form of methods and arrangements involving a filter implementation that factors in the time difference between consecutive searches for the same signal. Such an implementation modifies the coefficients of the filter depending on the time-arrival differences of consecutive search results.
According to the present invention, one example application of such an implementation is directed to single pole filter. Since the impulse response of an ideal single pole filter is exponentially decaying, the implementation varies the forgetting factor in an exponentially decaying fashion with respect to the time difference between consecutive searches.
Another example application of the present invention is directed to a method for filtering a stream of data samples arriving asynchronously, i.e., at irregular intervals. In accordance with the present invention, after determining a relative arrival time of data sample sets in the stream of data samples, the method filters the data sample sets using value assignments that are exponentially weighted for the data sample sets, the data sample sets being weighted more than data sample sets arriving late.
A more particular aspect of the present invention is directed to a specific CDMA cellular application. In this application, a communications system includes a mobile station communicating with a plurality of base stations. The pilot search results are processed in the mobile station""s receiver to provide asynchronous samples of the search results for each PN code. These asynchronous samples are processed in respective filters by a filtering process which provide a relative arrival time of data sample sets in the stream of data samples and filters the data sample sets using value assignments that are exponentially weighted. The data sample sets are weighted more than data sample sets arriving late. The filtered search results are then processed conventionally in connection with a handoff between base stations. In a more specific implementation, the receiver arrangement includes a digital signal processor programmed and arranged to filter the sample data sets.
The above summary is not intended to provide an overview of all aspects of the present invention. Other aspects of the present invention are exemplified and described in connection with the detailed description.